1. Field of the Invention
The present invention relates to a method of performing real-time correction of a water stage forecast, and particularly to a method of performing real-time correction of a water stage forecast that can utilize a Time Series method and a Kalman filter to correct a predicted water stage of a lead time. The proposed method for the error forecast is developed based on the forecasts of water stages at the lead time and the estimated water stages at previous time steps during a storm event as well as the associated the forecast error. It is Noted that this significantly differs from the other approaches for correcting the forecasted water stages.
2. Description of the Prior Art
In human history, floods are one of the most severe risks to human life and property. Therefore, water stage forecasts play an important and essential role in real-time water stage (e.g. rivers, lakes, and so on) management, where the water stage forecasts include flood control, flood warnings, reservoir operation and river regulation. The water stage forecasts can increase a lead time applied to a quantitative precipitation forecast (QPF) of a transformation of rainfall into runoff and travel time in main rivers catchments. Therefore, real-time water stage forecast, warning, and response systems aim to extend the lead time to people living on floodplains, so that they can take earlier action to save themselves and their property.
However, in any flood forecast system, uncertainty in the water stage forecast is caused by some factors (e.g. input uncertainty, model structure uncertainty, and parameter uncertainty). Therefore, because of the intrinsic uncertainty of meteorological forecasts, rainfall uncertainty (a type of input uncertainty) has more significant influence on the water stage forecast than other types of uncertainty (that is, the model structure uncertainty and the parameter uncertainty). In addition, the input uncertainty contributes inherent uncertainty in hydrologic and dynamic flow models that adds to the model structure uncertainty and the parameter uncertainty.
To sum up, reliability of the water stage forecast tends to decrease with increase of the lead time. That is to say, uncertainty in the water stage forecast generally increases with a lead time for implementing flood protection measures, so that the simulated and forecasted hydrographs may not perfectly fit the hydrographic measurements. Therefore, a water stage forecast provided by the prior art may not meet water stage forecast requirements for humanity.